As organizations look to get smarter and more agile in how they gain value and insight from their data, they are now able to take advantage of a fundamental shift in architecture. In the last decade, as an industry, we have gone from monolithic machines with direct-attached storage to VMs to cloud. The main attraction of cloud is due to its separation of compute and storage – a major architectural shift in the infrastructure layer that changes the way data can be stored and processed. Decoupling the two makes it easier for companies to analyze data in real-time while offering increased scalability, agility, availability at a lower cost. This is where the real value of cloud comes in – it allows organizations to focus less on their infrastructure and more on how they can realize business outcomes from their data.
While the cloud brings immense benefits, the process of modernizing enterprise platforms has its challenges. In working with over 1000 organizations to help them drive value from their data, we’ve seen common themes in our customers’ challenges as they journey from legacy platforms to public cloud.
Moving data between cloud and on-prem, or between cloud providers is expensive and labor-intensive to run and keep data updated. Managing the infrastructure and resources needed to support an analytics platform on-prem can be a burden for an organization. Data needs to be collocated with the workloads that run against it.
Leveraging cloud as IaaS
While cloud infrastructure as a service is a first step on the path to cloud, organizations who make this move as a way to benefit from the cost savings of cloud find that this model doesn’t allow them the elasticity or agility of cloud nor does it add up to the cost savings they would get from a true consumption model and cloud-native architecture, where features like auto-scaling can significantly reduce consumptions costs and improve performance.
Cloud point solutions are often implemented as a result of shadow IT for specific needs and can introduce tremendous security and compliance risks, and significant cost. These approaches often lock data into a single workload or vendor, leading to complex integration and (data) engineering to perform multi-workload analytics.
CDP Public Cloud is a cloud-native hybrid data architecture that is easy to deploy, manage, and use. By simplifying operations, CDP reduces the time to onboard new use cases across the organization. It delivers powerful, self-service analytics across hybrid and multi-cloud environments with the granular security and governance policies that IT leaders require to keep their organizations’ data safe. CDP Public Cloud provides integrated, elastic services that enable the rapid onboarding of use cases and efficient use of cloud infrastructure, reducing costs dramatically while offering self-service for data users.
Our CLOUDSMART offering provides the complete spectrum of services your organization needs to address everything from strategy to assessment and implementation assistance for successful CDP adoption. Our cloud experts help you de-risk the process of migrating to cloud. The result is a seamless and end-to-end data cloud experience that maintains existing SLAs and ensures ROI.
With a structured process and tools, Cloudera analyzes your workloads (ranging from ingestion to data engineering, data warehousing, analytics and information delivery) including resource utilization, performance, security, SLAs and cost. With these insights, we can identify cloud-friendly workloads by taking into account ease of migration execution, business impact, complexity, and ROI. Once reviewed and agreed, Cloudera then also executes the migration using a proven analytics workload migration framework and best practices.
To find out more about Cloudera’s CloudSmart packaged service and how it can help you accelerate your journey to the cloud, watch our “Scale Analytics with Confidence in Public Cloud” webinar.